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Description
What you’ll Learn:
- Digital Signal
Digital signal processing fundamentals and the numerical.
The fundamental concepts on Fourier Transforms
Root concepts like signals, noise, convolution, quantization, sampling. and many more
Complex concepts and their numerical like FFT, DIT-FFT made easy for you.
- Image Processing
Starting from basic 2-D images and getting into complex processing algorithms.
Numerical based on image segmentation, Histogram , Grey level & Zero memory point operations.Digital Signal processing has a vast background comprising of signals, their fundamental properties, and their applications in the real world. This course offers tutorials on the subject as a whole with in-line explanation and handy .pdf notes.
Images being the easiest way of getting information across, starting from artistic to marketing. And today, images are digital. So, it's important to know about image processing tasks including image enhancement, filtering, and image compression which are covered thoroughly.
Along with a pdf with important notes and explanations
Modules Covered:
Discrete-Time Signal /System
Discrete Fourier Transform
Fast Fourier Transform
Digital Image fundamentals
Image Enhancement
Image Segmentation -
How to Pass DSIP
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Discrete-Time Signal and Discrete-Time System
- Introduction to Digital Signal Processing
- Determine signal is periodic or aperiodic
- Determine signal is linear or non-linear
- Determine Signal is Time varient or Invarient
- Determine Signal is Static or Dynamic
- Determine Signal is Causal or Non Causal
- Determine Signal is Stable and Unstable
- Find Linear Convolution Part #1
- Find Linear Convolution Part #2
- Circular Convolution
- Cross Correlation and Auto Correlation
- Energy and Power Signal
- Types of Signals
- Stability Sum (find the range of linear time invariant signal for which impulse response is stable)
- Output response (0.3 delta wala sum )
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Discrete Fourier Transform
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Fast Fourier Transform
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Doubt Solving Session
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Digital Image Fundamentals
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Image Enhancement in Spatial domain
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Image Segmentation
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Image Processing New Video
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Digital Signal Processing Notes
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Image Processing Notes
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DSIP Notes
Convolution , Mask and Filtering
Convolution, Mask and Filtering
In image processing, convolution is the process of transforming an image by applying a kernel over each pixel and its local neighbors across the entire image. The kernel is a matrix of values whose size and values determine the transformation effect of the convolution process. Mask is a type of filter which performs operation directly on the image. The filter mask is also known as convolution mask. To apply a mask on an image, filter mask is moved point to point on the image. In the original image, at each point(X, Y), filter is calculated by using a predefined relationship.
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